// The agentic core. The plugin (not the host model) drives a loaded chat LLM
// through the AGENTS.md workflows: extract → compose (ingest), synthesise
// (query), review (lint). All LLM calls demand strict JSON we parse defensively.

import type { LMStudioClient, LLM } from "@lmstudio/sdk";

export interface PickedChat {
  model: LLM;
  identifier: string;
}

export async function pickChatModel(
  client: LMStudioClient,
  override: string,
): Promise<PickedChat | { error: string }> {
  if (override && override.trim()) {
    try {
      const model = await client.llm.model(override.trim());
      return { model, identifier: override.trim() };
    } catch (e: unknown) {
      return {
        error:
          `Failed to access the configured chat model "${override}". ` +
          `Check the identifier or load it in LM Studio. ` +
          `(${e instanceof Error ? e.message : String(e)})`,
      };
    }
  }
  const loaded = await client.llm.listLoaded();
  if (loaded.length === 0) {
    return { error: "No chat LLM is currently loaded in LM Studio. Load one and try again." };
  }
  // Prefer a non-vision text model, but fall back to whatever is loaded.
  const text = loaded.find((m) => m.vision !== true) ?? loaded[0];
  let identifier = "(loaded LLM)";
  try {
    const info = await text.getModelInfo();
    identifier = info?.identifier ?? info?.modelKey ?? identifier;
  } catch {
    /* keep fallback */
  }
  return { model: text, identifier };
}

const JSON_RULES =
  "Respond with ONE valid JSON object and NOTHING else — no prose, no markdown " +
  "fences, no comments. Use double quotes. Do not invent facts or citations; if " +
  "the source does not support a claim, omit it.";

function extractJson(raw: string): unknown {
  let s = raw.trim();
  // strip ```json ... ``` fences if present
  const fence = s.match(/```(?:json)?\s*([\s\S]*?)```/i);
  if (fence) s = fence[1].trim();
  // fall back to the outermost { ... }
  if (!s.startsWith("{")) {
    const first = s.indexOf("{");
    const last = s.lastIndexOf("}");
    if (first >= 0 && last > first) s = s.slice(first, last + 1);
  }
  return JSON.parse(s);
}

export interface RunJsonArgs {
  model: LLM;
  system: string;
  user: string;
  abortSignal: AbortSignal;
  maxTokens?: number;
  /** JSON schema constraining the output. Strongly recommended — it forces the
   *  model to emit valid, conformant JSON (grammar-constrained decoding). */
  jsonSchema?: unknown;
}

/** Call the model and parse strict JSON, with one corrective retry. */
export async function runJson<T>(args: RunJsonArgs): Promise<T> {
  const structured = args.jsonSchema
    ? { type: "json" as const, jsonSchema: args.jsonSchema }
    : { type: "json" as const };
  const call = async (extra: string): Promise<string> => {
    const res = await args.model.respond(
      [
        { role: "system", content: `${args.system}\n\n${JSON_RULES}${extra}` },
        { role: "user", content: args.user },
      ],
      { temperature: 0.2, maxTokens: args.maxTokens ?? 4096, signal: args.abortSignal, structured },
    );
    return res.content;
  };
  let last = "";
  try {
    last = await call("");
    return extractJson(last) as T;
  } catch (e1) {
    // one retry, nudging harder
    try {
      last = await call("\nYour previous output was not valid JSON. Output ONLY the JSON object.");
      return extractJson(last) as T;
    } catch (e2) {
      const snippet = last.slice(0, 400).replace(/\s+/g, " ").trim();
      throw new Error(
        `The chat model did not return valid JSON for this step. This usually means the loaded ` +
          `model is too small or does not support structured output — try a larger, tool/JSON-capable ` +
          `instruct model. Last output (truncated): "${snippet}"`,
      );
    }
  }
}

// ---------------------------------------------------------------------------
// INGEST — step 1: extract the entities/concepts the source touches
// ---------------------------------------------------------------------------

export interface ExtractResult {
  entities: Array<{ slug: string; name: string }>;
  concepts: Array<{ slug: string; name: string }>;
}

const slugNameArray = {
  type: "array",
  items: {
    type: "object",
    properties: { slug: { type: "string" }, name: { type: "string" } },
    required: ["slug", "name"],
  },
} as const;

export const EXTRACT_SCHEMA = {
  type: "object",
  properties: { entities: slugNameArray, concepts: slugNameArray },
  required: ["entities", "concepts"],
} as const;

export function buildExtractPrompt(
  schema: string,
  sourceTitle: string,
  sourceText: string,
): { system: string; user: string; jsonSchema: unknown } {
  const built = {
    system:
      "Tu es un mainteneur de wiki discipliné (voir le schéma ci-dessous). " +
      "Lis la source et liste UNIQUEMENT les entités (personnes, lieux, orgs, produits) " +
      "et les concepts/thèmes qui méritent une page de wiki. Donne un slug kebab-case " +
      "sans accent pour chacun.\n\n# Schéma (extrait)\n" +
      truncate(schema, 2500) +
      '\n\nFormat JSON attendu : {"entities":[{"slug":"","name":""}],"concepts":[{"slug":"","name":""}]}',
    user: `# Source : ${sourceTitle}\n\n${truncate(sourceText, 12000)}`,
  };
  return { ...built, jsonSchema: EXTRACT_SCHEMA };
}

// ---------------------------------------------------------------------------
// INGEST — step 2: compose the source page + create/merge entity/concept pages
// ---------------------------------------------------------------------------

export interface ComposedPage {
  path: string; // relative to wiki/, e.g. "entities/marie-curie.md"
  action: "create" | "update";
  markdown: string; // FULL page content (frontmatter + body)
  reason?: string;
}

export interface ComposeResult {
  source_page: { path: string; markdown: string };
  pages: ComposedPage[];
  contradictions: string[];
  log_bullets: string[];
  notes: string[];
}

export interface ExistingPage {
  path: string; // relative to wiki/
  content: string;
}

const stringArray = { type: "array", items: { type: "string" } } as const;

export const COMPOSE_SCHEMA = {
  type: "object",
  properties: {
    source_page: {
      type: "object",
      properties: { path: { type: "string" }, markdown: { type: "string" } },
      required: ["path", "markdown"],
    },
    pages: {
      type: "array",
      items: {
        type: "object",
        properties: {
          path: { type: "string" },
          action: { type: "string" },
          markdown: { type: "string" },
          reason: { type: "string" },
        },
        required: ["path", "action", "markdown"],
      },
    },
    contradictions: stringArray,
    log_bullets: stringArray,
    notes: stringArray,
  },
  required: ["source_page", "pages"],
} as const;

export function buildComposePrompt(
  schema: string,
  sourceFileRel: string,
  sourceTitle: string,
  sourceText: string,
  indexHead: string,
  existingPages: ExistingPage[],
  today: string,
): { system: string; user: string; jsonSchema: unknown } {
  const existingBlock = existingPages.length
    ? existingPages
        .map((p) => `### Page existante : ${p.path}\n\n${truncate(p.content, 3000)}`)
        .join("\n\n")
    : "(aucune page existante à fusionner)";

  const system =
    "Tu es un mainteneur de wiki discipliné. Tu appliques STRICTEMENT le schéma ci-dessous " +
    "(frontmatter YAML, wikilinks [[slug]], une page par entité/concept, citations, " +
    "signaler les contradictions sans écraser). Tu produis le contenu COMPLET de chaque page.\n\n" +
    "Règles de fusion : pour une page existante fournie, RENVOIE la page entière mise à jour " +
    "(intègre les nouveaux faits, ajoute le slug de la source à `sources:`, mets à jour " +
    "`last_updated`, ajoute les wikilinks utiles) — ne supprime pas l'existant. " +
    "Pour une nouvelle page, crée-la au format du schéma.\n\n" +
    "IMPÉRATIF — frontmatter YAML VALIDE : les listes s'écrivent en style flow sur UNE ligne, " +
    "ex. `sources: [source-a, source-b]`, `tags: [x, y]`, `aliases: []` (JAMAIS `sources: - a`). " +
    "Mets les valeurs texte entre guillemets si elles contiennent `:` ou des accents. " +
    "Les dates au format AAAA-MM-JJ. Le bloc frontmatter est délimité par `---`.\n\n# Schéma\n" +
    truncate(schema, 4000) +
    "\n\n# Format JSON attendu\n" +
    '{"source_page":{"path":"sources/<slug>.md","markdown":"..."},' +
    '"pages":[{"path":"entities/<slug>.md","action":"create|update","markdown":"...","reason":""}],' +
    '"contradictions":["..."],"log_bullets":["..."],"notes":["..."]}';

  const user =
    `Date du jour : ${today}\n` +
    `Fichier source brut : raw/${sourceFileRel}\n` +
    `Titre : ${sourceTitle}\n\n` +
    `# Catalogue actuel (index.md, extrait)\n${truncate(indexHead, 2500)}\n\n` +
    `# Pages existantes à fusionner\n${existingBlock}\n\n` +
    `# Contenu de la source\n${truncate(sourceText, 14000)}`;

  return { system, user, jsonSchema: COMPOSE_SCHEMA };
}

// ---------------------------------------------------------------------------
// QUERY — synthesise a cited answer from retrieved passages
// ---------------------------------------------------------------------------

export interface QueryResult {
  answer_markdown: string;
  file_as_analysis: boolean;
  analysis?: { slug: string; title: string; markdown: string };
  log_note: string;
}

export interface RetrievedPassage {
  wikilink: string;
  headingPath: string[];
  snippet: string;
}

export const QUERY_SCHEMA = {
  type: "object",
  properties: {
    answer_markdown: { type: "string" },
    file_as_analysis: { type: "boolean" },
    analysis: {
      type: "object",
      properties: { slug: { type: "string" }, title: { type: "string" }, markdown: { type: "string" } },
    },
    log_note: { type: "string" },
  },
  required: ["answer_markdown", "file_as_analysis"],
} as const;

export function buildQueryPrompt(
  schema: string,
  question: string,
  passages: RetrievedPassage[],
  today: string,
): { system: string; user: string; jsonSchema: unknown } {
  const ctx = passages.length
    ? passages
        .map(
          (p, i) =>
            `[${i + 1}] [[${p.wikilink}]]${p.headingPath.length ? " › " + p.headingPath.join(" › ") : ""}\n${p.snippet}`,
        )
        .join("\n\n")
    : "(aucun passage trouvé dans le wiki)";

  const system =
    "Tu réponds à une question en t'appuyant UNIQUEMENT sur les passages du wiki fournis. " +
    "Chaque affirmation doit être citée avec le wikilink [[...]] de sa source. Si les passages " +
    "ne suffisent pas, dis-le explicitement (ne fabrique rien). Si la réponse a une valeur " +
    "durable (comparaison, synthèse, connexion), propose de la classer comme page d'analyse " +
    "(file_as_analysis=true) au format du schéma.\n\n# Schéma (extrait)\n" +
    truncate(schema, 2000) +
    "\n\n# Format JSON attendu\n" +
    '{"answer_markdown":"...","file_as_analysis":false,' +
    '"analysis":{"slug":"","title":"","markdown":""},"log_note":"..."}';

  const user = `Date : ${today}\n\n# Question\n${question}\n\n# Passages du wiki (RAG)\n${ctx}`;
  return { system, user, jsonSchema: QUERY_SCHEMA };
}

// ---------------------------------------------------------------------------
// LINT — find contradictions, stale claims, gaps, suggestions
// ---------------------------------------------------------------------------

export interface LintResult {
  findings: Array<{ type: string; severity: "info" | "warn" | "high"; page?: string; detail: string }>;
  suggestions: string[];
}

export const LINT_SCHEMA = {
  type: "object",
  properties: {
    findings: {
      type: "array",
      items: {
        type: "object",
        properties: {
          type: { type: "string" },
          severity: { type: "string" },
          page: { type: "string" },
          detail: { type: "string" },
        },
        required: ["type", "detail"],
      },
    },
    suggestions: { type: "array", items: { type: "string" } },
  },
  required: ["findings", "suggestions"],
} as const;

export function buildLintPrompt(
  schema: string,
  pageSummaries: Array<{ path: string; title: string; outbound: string[]; inbound: number }>,
  structuralNotes: string[],
): { system: string; user: string; jsonSchema: unknown } {
  const pages = pageSummaries
    .map(
      (p) =>
        `- ${p.path} — « ${p.title} » | liens sortants: ${p.outbound.length} | liens entrants: ${p.inbound}`,
    )
    .join("\n");

  const system =
    "Tu fais un contrôle de santé du wiki. À partir du catalogue et des notes structurelles " +
    "déjà calculées, identifie : contradictions entre pages, affirmations vraisemblablement " +
    "périmées, concepts importants sans page dédiée, références croisées manquantes, lacunes " +
    "de données. Propose aussi des questions à explorer et des sources à chercher. Sois concret " +
    "et bref.\n\n# Schéma (extrait)\n" +
    truncate(schema, 1500) +
    "\n\n# Format JSON attendu\n" +
    '{"findings":[{"type":"","severity":"info|warn|high","page":"","detail":""}],"suggestions":["..."]}';

  const user =
    `# Catalogue des pages\n${pages || "(wiki vide)"}\n\n` +
    `# Notes structurelles déjà détectées\n${structuralNotes.length ? structuralNotes.map((n) => `- ${n}`).join("\n") : "(aucune)"}`;
  return { system, user, jsonSchema: LINT_SCHEMA };
}

// ---------------------------------------------------------------------------

function truncate(s: string, max: number): string {
  if (s.length <= max) return s;
  return s.slice(0, max) + `\n…[tronqué ${s.length - max} caractères]`;
}

// The agentic core. The plugin (not the host model) drives a loaded chat LLM
// through the AGENTS.md workflows: extract → compose (ingest), synthesise
// (query), review (lint). All LLM calls demand strict JSON we parse defensively.

import type { LMStudioClient, LLM } from "@lmstudio/sdk";

export interface PickedChat {
  model: LLM;
  identifier: string;
}

export async function pickChatModel(
  client: LMStudioClient,
  override: string,
): Promise<PickedChat | { error: string }> {
  if (override && override.trim()) {
    try {
      const model = await client.llm.model(override.trim());
      return { model, identifier: override.trim() };
    } catch (e: unknown) {
      return {
        error:
          `Failed to access the configured chat model "${override}". ` +
          `Check the identifier or load it in LM Studio. ` +
          `(${e instanceof Error ? e.message : String(e)})`,
      };
    }
  }
  const loaded = await client.llm.listLoaded();
  if (loaded.length === 0) {
    return { error: "No chat LLM is currently loaded in LM Studio. Load one and try again." };
  }
  // Prefer a non-vision text model, but fall back to whatever is loaded.
  const text = loaded.find((m) => m.vision !== true) ?? loaded[0];
  let identifier = "(loaded LLM)";
  try {
    const info = await text.getModelInfo();
    identifier = info?.identifier ?? info?.modelKey ?? identifier;
  } catch {
    /* keep fallback */
  }
  return { model: text, identifier };
}

const JSON_RULES =
  "Respond with ONE valid JSON object and NOTHING else — no prose, no markdown " +
  "fences, no comments. Use double quotes. Do not invent facts or citations; if " +
  "the source does not support a claim, omit it.";

function extractJson(raw: string): unknown {
  let s = raw.trim();
  // strip ```json ... ``` fences if present
  const fence = s.match(/```(?:json)?\s*([\s\S]*?)```/i);
  if (fence) s = fence[1].trim();
  // fall back to the outermost { ... }
  if (!s.startsWith("{")) {
    const first = s.indexOf("{");
    const last = s.lastIndexOf("}");
    if (first >= 0 && last > first) s = s.slice(first, last + 1);
  }
  return JSON.parse(s);
}

export interface RunJsonArgs {
  model: LLM;
  system: string;
  user: string;
  abortSignal: AbortSignal;
  maxTokens?: number;
  /** JSON schema constraining the output. Strongly recommended — it forces the
   *  model to emit valid, conformant JSON (grammar-constrained decoding). */
  jsonSchema?: unknown;
}

/** Call the model and parse strict JSON, with one corrective retry. */
export async function runJson<T>(args: RunJsonArgs): Promise<T> {
  const structured = args.jsonSchema
    ? { type: "json" as const, jsonSchema: args.jsonSchema }
    : { type: "json" as const };
  const call = async (extra: string): Promise<string> => {
    const res = await args.model.respond(
      [
        { role: "system", content: `${args.system}\n\n${JSON_RULES}${extra}` },
        { role: "user", content: args.user },
      ],
      { temperature: 0.2, maxTokens: args.maxTokens ?? 4096, signal: args.abortSignal, structured },
    );
    return res.content;
  };
  let last = "";
  try {
    last = await call("");
    return extractJson(last) as T;
  } catch (e1) {
    // one retry, nudging harder
    try {
      last = await call("\nYour previous output was not valid JSON. Output ONLY the JSON object.");
      return extractJson(last) as T;
    } catch (e2) {
      const snippet = last.slice(0, 400).replace(/\s+/g, " ").trim();
      throw new Error(
        `The chat model did not return valid JSON for this step. This usually means the loaded ` +
          `model is too small or does not support structured output — try a larger, tool/JSON-capable ` +
          `instruct model. Last output (truncated): "${snippet}"`,
      );
    }
  }
}

// ---------------------------------------------------------------------------
// INGEST — step 1: extract the entities/concepts the source touches
// ---------------------------------------------------------------------------

export interface ExtractResult {
  entities: Array<{ slug: string; name: string }>;
  concepts: Array<{ slug: string; name: string }>;
}

const slugNameArray = {
  type: "array",
  items: {
    type: "object",
    properties: { slug: { type: "string" }, name: { type: "string" } },
    required: ["slug", "name"],
  },
} as const;

export const EXTRACT_SCHEMA = {
  type: "object",
  properties: { entities: slugNameArray, concepts: slugNameArray },
  required: ["entities", "concepts"],
} as const;

export function buildExtractPrompt(
  schema: string,
  sourceTitle: string,
  sourceText: string,
): { system: string; user: string; jsonSchema: unknown } {
  const built = {
    system:
      "Tu es un mainteneur de wiki discipliné (voir le schéma ci-dessous). " +
      "Lis la source et liste UNIQUEMENT les entités (personnes, lieux, orgs, produits) " +
      "et les concepts/thèmes qui méritent une page de wiki. Donne un slug kebab-case " +
      "sans accent pour chacun.\n\n# Schéma (extrait)\n" +
      truncate(schema, 2500) +
      '\n\nFormat JSON attendu : {"entities":[{"slug":"","name":""}],"concepts":[{"slug":"","name":""}]}',
    user: `# Source : ${sourceTitle}\n\n${truncate(sourceText, 12000)}`,
  };
  return { ...built, jsonSchema: EXTRACT_SCHEMA };
}

// ---------------------------------------------------------------------------
// INGEST — step 2: compose the source page + create/merge entity/concept pages
// ---------------------------------------------------------------------------

export interface ComposedPage {
  path: string; // relative to wiki/, e.g. "entities/marie-curie.md"
  action: "create" | "update";
  markdown: string; // FULL page content (frontmatter + body)
  reason?: string;
}

export interface ComposeResult {
  source_page: { path: string; markdown: string };
  pages: ComposedPage[];
  contradictions: string[];
  log_bullets: string[];
  notes: string[];
}

export interface ExistingPage {
  path: string; // relative to wiki/
  content: string;
}

const stringArray = { type: "array", items: { type: "string" } } as const;

export const COMPOSE_SCHEMA = {
  type: "object",
  properties: {
    source_page: {
      type: "object",
      properties: { path: { type: "string" }, markdown: { type: "string" } },
      required: ["path", "markdown"],
    },
    pages: {
      type: "array",
      items: {
        type: "object",
        properties: {
          path: { type: "string" },
          action: { type: "string" },
          markdown: { type: "string" },
          reason: { type: "string" },
        },
        required: ["path", "action", "markdown"],
      },
    },
    contradictions: stringArray,
    log_bullets: stringArray,
    notes: stringArray,
  },
  required: ["source_page", "pages"],
} as const;

export function buildComposePrompt(
  schema: string,
  sourceFileRel: string,
  sourceTitle: string,
  sourceText: string,
  indexHead: string,
  existingPages: ExistingPage[],
  today: string,
): { system: string; user: string; jsonSchema: unknown } {
  const existingBlock = existingPages.length
    ? existingPages
        .map((p) => `### Page existante : ${p.path}\n\n${truncate(p.content, 3000)}`)
        .join("\n\n")
    : "(aucune page existante à fusionner)";

  const system =
    "Tu es un mainteneur de wiki discipliné. Tu appliques STRICTEMENT le schéma ci-dessous " +
    "(frontmatter YAML, wikilinks [[slug]], une page par entité/concept, citations, " +
    "signaler les contradictions sans écraser). Tu produis le contenu COMPLET de chaque page.\n\n" +
    "Règles de fusion : pour une page existante fournie, RENVOIE la page entière mise à jour " +
    "(intègre les nouveaux faits, ajoute le slug de la source à `sources:`, mets à jour " +
    "`last_updated`, ajoute les wikilinks utiles) — ne supprime pas l'existant. " +
    "Pour une nouvelle page, crée-la au format du schéma.\n\n" +
    "IMPÉRATIF — frontmatter YAML VALIDE : les listes s'écrivent en style flow sur UNE ligne, " +
    "ex. `sources: [source-a, source-b]`, `tags: [x, y]`, `aliases: []` (JAMAIS `sources: - a`). " +
    "Mets les valeurs texte entre guillemets si elles contiennent `:` ou des accents. " +
    "Les dates au format AAAA-MM-JJ. Le bloc frontmatter est délimité par `---`.\n\n# Schéma\n" +
    truncate(schema, 4000) +
    "\n\n# Format JSON attendu\n" +
    '{"source_page":{"path":"sources/<slug>.md","markdown":"..."},' +
    '"pages":[{"path":"entities/<slug>.md","action":"create|update","markdown":"...","reason":""}],' +
    '"contradictions":["..."],"log_bullets":["..."],"notes":["..."]}';

  const user =
    `Date du jour : ${today}\n` +
    `Fichier source brut : raw/${sourceFileRel}\n` +
    `Titre : ${sourceTitle}\n\n` +
    `# Catalogue actuel (index.md, extrait)\n${truncate(indexHead, 2500)}\n\n` +
    `# Pages existantes à fusionner\n${existingBlock}\n\n` +
    `# Contenu de la source\n${truncate(sourceText, 14000)}`;

  return { system, user, jsonSchema: COMPOSE_SCHEMA };
}

// ---------------------------------------------------------------------------
// QUERY — synthesise a cited answer from retrieved passages
// ---------------------------------------------------------------------------

export interface QueryResult {
  answer_markdown: string;
  file_as_analysis: boolean;
  analysis?: { slug: string; title: string; markdown: string };
  log_note: string;
}

export interface RetrievedPassage {
  wikilink: string;
  headingPath: string[];
  snippet: string;
}

export const QUERY_SCHEMA = {
  type: "object",
  properties: {
    answer_markdown: { type: "string" },
    file_as_analysis: { type: "boolean" },
    analysis: {
      type: "object",
      properties: { slug: { type: "string" }, title: { type: "string" }, markdown: { type: "string" } },
    },
    log_note: { type: "string" },
  },
  required: ["answer_markdown", "file_as_analysis"],
} as const;

export function buildQueryPrompt(
  schema: string,
  question: string,
  passages: RetrievedPassage[],
  today: string,
): { system: string; user: string; jsonSchema: unknown } {
  const ctx = passages.length
    ? passages
        .map(
          (p, i) =>
            `[${i + 1}] [[${p.wikilink}]]${p.headingPath.length ? " › " + p.headingPath.join(" › ") : ""}\n${p.snippet}`,
        )
        .join("\n\n")
    : "(aucun passage trouvé dans le wiki)";

  const system =
    "Tu réponds à une question en t'appuyant UNIQUEMENT sur les passages du wiki fournis. " +
    "Chaque affirmation doit être citée avec le wikilink [[...]] de sa source. Si les passages " +
    "ne suffisent pas, dis-le explicitement (ne fabrique rien). Si la réponse a une valeur " +
    "durable (comparaison, synthèse, connexion), propose de la classer comme page d'analyse " +
    "(file_as_analysis=true) au format du schéma.\n\n# Schéma (extrait)\n" +
    truncate(schema, 2000) +
    "\n\n# Format JSON attendu\n" +
    '{"answer_markdown":"...","file_as_analysis":false,' +
    '"analysis":{"slug":"","title":"","markdown":""},"log_note":"..."}';

  const user = `Date : ${today}\n\n# Question\n${question}\n\n# Passages du wiki (RAG)\n${ctx}`;
  return { system, user, jsonSchema: QUERY_SCHEMA };
}

// ---------------------------------------------------------------------------
// LINT — find contradictions, stale claims, gaps, suggestions
// ---------------------------------------------------------------------------

export interface LintResult {
  findings: Array<{ type: string; severity: "info" | "warn" | "high"; page?: string; detail: string }>;
  suggestions: string[];
}

export const LINT_SCHEMA = {
  type: "object",
  properties: {
    findings: {
      type: "array",
      items: {
        type: "object",
        properties: {
          type: { type: "string" },
          severity: { type: "string" },
          page: { type: "string" },
          detail: { type: "string" },
        },
        required: ["type", "detail"],
      },
    },
    suggestions: { type: "array", items: { type: "string" } },
  },
  required: ["findings", "suggestions"],
} as const;

export function buildLintPrompt(
  schema: string,
  pageSummaries: Array<{ path: string; title: string; outbound: string[]; inbound: number }>,
  structuralNotes: string[],
): { system: string; user: string; jsonSchema: unknown } {
  const pages = pageSummaries
    .map(
      (p) =>
        `- ${p.path} — « ${p.title} » | liens sortants: ${p.outbound.length} | liens entrants: ${p.inbound}`,
    )
    .join("\n");

  const system =
    "Tu fais un contrôle de santé du wiki. À partir du catalogue et des notes structurelles " +
    "déjà calculées, identifie : contradictions entre pages, affirmations vraisemblablement " +
    "périmées, concepts importants sans page dédiée, références croisées manquantes, lacunes " +
    "de données. Propose aussi des questions à explorer et des sources à chercher. Sois concret " +
    "et bref.\n\n# Schéma (extrait)\n" +
    truncate(schema, 1500) +
    "\n\n# Format JSON attendu\n" +
    '{"findings":[{"type":"","severity":"info|warn|high","page":"","detail":""}],"suggestions":["..."]}';

  const user =
    `# Catalogue des pages\n${pages || "(wiki vide)"}\n\n` +
    `# Notes structurelles déjà détectées\n${structuralNotes.length ? structuralNotes.map((n) => `- ${n}`).join("\n") : "(aucune)"}`;
  return { system, user, jsonSchema: LINT_SCHEMA };
}

// ---------------------------------------------------------------------------

function truncate(s: string, max: number): string {
  if (s.length <= max) return s;
  return s.slice(0, max) + `\n…[tronqué ${s.length - max} caractères]`;
}